Information is stored and presented in many ways. In some instances it is stored simply as a mass of individual items within a collection. In this case, finding Information involves searching, generally through the use of keywords or phrases.
The problem with this type of searching is that it can produce unmanageable numbers of hits, most of which are irrelevant or outdated, thus inundating the user. Additionally, information sources that do not contain the keywords but which are nonetheless relevant are missed through this type of information gathering.
In order to overcome the above difficulties, various attempts to organize knowledge have been attempted. A common method of organizing information is through the use of a hierarchical category system. In this type of system a category is created, and various subcategories fall within the category. Each of these subcategories may further have subcategories under it, and so forth, creating a tree like structure.
This hierarchical structure can for example be seen in U.S. Pat. No. 6,112,201 to Wicul. Wicul teaches a structure in which documents are stored in a hierarchical structure and information is classified based on a number of predefined categories. In categorical groupings, information can be placed within a predefined tree of categories in such a way that a user looking for specific information may navigate starting at the root and moving through the leaves of the tree. For example, in a broad database of information, if a user is looking for information about Formula 1 racing in an information database, the user starts at the root. The user may be presented with various categories, such as Arts, Business, Computers, Games, or Sports The most relevant category in this case is Sports, which when selected may lead the user to a list of various sports, the most relevant being Motorsports. When selected, this category may further lead to a number of subcategories about motor sports. The user would thus proceed until the desired subcategory is found.
The problem with a hierarchical arrangement of knowledge elements is that related subjects will often not be present Within the same hierarchical category, or even the same branch of a tree. In the above example, a user may find a Formula 1 race that she is interested in, and then want more information about the venue city, such as places to stay or eat. This information does not however fall within the category of SPORTS>MOTORSPORTS>AUTO RACING>FORMULA 1. While this information is related, it would not be proper to create a subcategory for the venue city here, and the user will thus have to commence a new search.
Another problem with storing knowledge elements in a hierarchical structure is that a knowledge element may properly fit at various points within the tree. This knowledge element is thus placed in these various locations, and as long as it does not change there is no problem. However, if the knowledge element is modified or removed, the tree will have to be modified at every instance of the knowledge node, which can be an onerous task. Also, with this type of structure stale nodes will often be missed, leaving outdated information within the tree.
A further problem with this hierarchical structure is that the root is preset. In an ideal search environment, the root would be the knowledge element the user is interested in, thus allowing the user to navigate through related knowledge elements without having to perform a new search. However, the hierarchical structure presents a rigid arrangement for knowledge elements which limits information gathering by the user.